Friday, February 6, 2026

AI Capex is a Time-Tested Moat-Building Move

Investors might be quite concerned about the vast expansion of capital investment being made by some hyperscalers to support their artificial intelligence aspirations. 


But there is an established logic here that has played out in the past in the computing industry: high capital expenditure is one of the most formidable barriers to entry in the computing industry, particularly in semiconductors, cloud infrastructure, and AI. 


The strategy also is evident in other industries and domains. 


source: Bloomberg


This is rational, though concerning to many investors. 


Dominant firms with access to massive capital can make enormous infrastructure investments that raise the minimum viable scale for competition. 


This creates a self-reinforcing cycle where competitors must either match the investment to remain relevant or accept a permanent competitive disadvantage. 


Eventually, the capital requirements become so extreme that new entrants are effectively locked out, and smaller competitors are forced to exit or consolidate. The strategic value to hyperscalers includes:

  • Preemptive positioning: By building capacity ahead of demand, they occupy strategic positions before competitors can respond.

  • Credible commitment: Massive sunk costs signal to competitors and investors that the incumbent won't easily retreat from the market.

  • Economies of scale: Higher fixed costs create steeper learning curves and better unit economics that smaller players can't match.

  • Talent and supplier lock-in: Large capex programs secure scarce engineering talent and manufacturing capacity.


Jensen Huang, Nvidia CEO, has emphasized that scale in AI computing creates "moats" that are difficult to cross. And, in recent days, we have seen hyperscale cloud providers routinely announce capex figures in earnings calls as competitive signals. 


Semiconductor executives also have explicitly discussed capacity additions as deterrents to new fab construction by competitors.


Sector

Companies

Capex Scale

Barrier Effect

Potential Strategic Element

Semiconductor Fabs

TSMC advanced nodes

$30-40B per advanced fab; ~$100B total 2023-2025

Only 3 companies globally can produce leading-edge chips (TSMC, Samsung, Intel)

TSMC's aggressive capacity expansion maintains 50%+ market share; timing announcements ahead of Samsung

AI Infrastructure

Microsoft/OpenAI

$100B+ planned over multiple years for AI datacenters

Creates computational advantage for training frontier models

Announced investments signal to competitors the scale needed to compete in AI

Cloud Computing

AWS, Azure, GCP

$50-60B annually each in datacenter capex

Requires global footprint of datacenters; new entrants can't match geographic coverage

Continuous expansion makes it economically irrational for new hyperscalers to emerge

GPU Manufacturing

NVIDIA

$11B+ in datacenter infrastructure (2023)

Combined with CUDA ecosystem, creates vertical integration barrier

Aggressive pre-positioning before AI boom locked in supply chain

Memory Manufacturing

Samsung, SK Hynix, Micron

$20-40B per company annually

Only 3 major DRAM producers remain after consolidation

Counter-cyclical investment during downturns forces exits by weaker players

EUV Lithography

ASML

€6B+ R&D over decades; €20B+ facilities

Single supplier globally; complete monopoly

Not replicable by competitors; 30+ year moat

Custom Silicon

Google TPU program

Multi-billion dollar investment in custom ASICs

Vertical integration advantage in AI/ML workloads

Reduces dependence on NVIDIA; raises bar for cloud competitors

Hyperscale Datacenters

Meta

$28-37B capex guidance (2024)

AI training and inference infrastructure

Explicit strategy to build capacity exceeding near-term needs


So there is a rational logic at work here. The computing industry increasingly resembles other capital-intensive industries such as aerospace or pharmaceuticals, where high barriers to entry lead to oligopolistic market structures


Investing now increases the odds that a particular hyperscaler will emerge as a leader when the industry matures. 


Historians might note that the principle works in other spheres of life as well. President Ronald Reagan, for example, deliberately provoked an arms race with the Soviet Union, betting that the USSR could not keep up. He won that bet. 


Nor is the strategy unusual. 


The logic of "investment wars" operates across many domains. The underlying principle is the same: those with access to capital can raise the stakes so high that potential competitors are priced out of meaningful participation.


In each case, the dominant actor exploits asymmetric access to resources to:

  1. Raise minimum viable scale beyond what most competitors can afford

  2. Create psychological deterrence by signaling overwhelming commitment

  3. Lock in strategic assets (talent, infrastructure, relationships) before competitors can mobilize

  4. Force attrition by making competition economically irrational

  5. Establish self-reinforcing advantages where initial spending generates returns that fund further spending.


Domain

Example

Spending Scale

Mechanism

Effect

US Presidential Politics

Bloomberg 2020 primary

$1B+ on single primary campaign

Saturated airwaves in every market; hired most available campaign talent

Made it financially impossible for lower-tier candidates to get message out; hired away potential staff for other campaigns

English Football

Manchester City (2008-present)

£1.5B+ in transfers/wages over 15 years

Acquired multiple elite players per position; highest wage bill in league

Created squad depth no competitor could match; forced other clubs into unsustainable wage escalation or acceptance of second-tier status

Streaming Wars

Netflix content spending

$17B annually on content (peak)

Commissioned content at scale competitors couldn't initially match

Locked up production capacity, talent deals, and viewer attention before Disney+/HBO Max fully scaled

Formula 1 Racing

Mercedes-AMG (2014-2020)

£300-400M annually (estimated total budget)

Outspent rivals on R&D, wind tunnel time, personnel

Seven consecutive constructors' championships; competitors couldn't catch up until budget cap imposed in 2021

US Senate Races

Super PAC spending in competitive states

$100M+ per competitive seat (2022)

Unlimited independent expenditure on advertising

Drowns out candidates without billionaire backing; forces defensive spending that depletes resources

College Football

SEC conference arms race

$200-400M facilities per school

Built palatial training facilities, stadiums, practice complexes

Recruiting advantage over schools that can't match; forces other conferences into similar spending or accept talent disadvantage

Pharmaceutical R&D

Big Pharma lobbying/marketing

$30-50M per major drug launch marketing

Saturates physician networks, conferences, and media before generics or competitors launch

Generic manufacturers can't match brand awareness; biosimilar uptake slowed despite cost advantages

Local News Markets

Sinclair Broadcasting acquisitions

$10B+ in station acquisitions

Bought multiple stations per market, achieving economies of scale in production

Local independent stations can't compete on costs; consolidation reduces viewpoint diversity

Premier League Broadcasting

Sky Sports bid wars (1990s-2000s)

£5B+ for three-year rights packages

Outbid terrestrial broadcasters by massive margins

Made football unaffordable for free-to-air TV; entrenched pay-TV model

US House Races

DCCC/NRCC spending in swing districts

$5-10M per competitive district

Party committees flood districts with ads, staff, and ground operations

Self-funded or grassroots candidates can't compete for voter attention

NBA Team Building

Brooklyn Nets "super team" (2021)

$200M+ luxury tax payroll

Acquired three max-contract superstars simultaneously

Only teams with billionaire owners willing to absorb luxury tax could compete; small-market teams structurally disadvantaged

Political Consulting

Top-tier presidential campaigns

$50-100M on consultants, data, analytics

Hire all top-tier strategists, pollsters, data scientists

Credible challengers struggle to assemble competitive teams; talent locked up years in advance

Spanish Football

Real Madrid Galacticos strategy

€1B+ on superstar transfers (2000-2009)

Signed most marketable players globally (Beckham, Ronaldo, Zidane, etc.)

Commercial revenue advantages compound; smaller clubs become feeder systems

US Gubernatorial Races

Self-funding billionaire candidates

$50-100M+ personal funds

Bypass fundraising entirely; saturate media markets

Traditional politicians can't match spending; discourages viable challengers from entering

Media Acquisitions

Comcast/NBC Universal merger

$30B acquisition

Vertical integration of content production and distribution

Competitors without both production and distribution at scale disadvantaged

Olympics Bidding

Major city Olympic bids

$10-20B infrastructure commitments

Build stadiums, transit, housing before winning bid

Only wealthy nations/cities can credibly bid; developing nations priced out

Political Ground Game

Georgia Senate runoffs (2021)

$500M+ combined on both races

Hired thousands of canvassers; multiple field offices per county

Created field operation competitors couldn't match in timeline available

College Basketball

Duke/Kentucky facilities/NIL

$100M+ practice facilities; uncapped NIL deals

Built NBA-caliber practice facilities; boosters fund unlimited NIL payments

Mid-major programs can't retain top recruits even if they develop them

Super Bowl Advertising

Major brands buying multiple spots

$30-50M for multi-ad presence

Buy 4-6 slots in single game

Smaller brands can't afford even single spot; attention monopolized by incumbents


These examples demonstrate several variations on the core theme:

  • Preemptive capacity building: Netflix's content spending, NFL stadium construction, and college athletic facilities all involve building ahead of immediate need to lock in advantages.

  • Talent hoarding: Political campaigns hiring all available consultants, sports teams signing players beyond roster needs, and media companies locking up producers all prevent competitors from accessing critical human capital.

  • Attention monopolization: Super Bowl advertisers, political ad spending, and streaming content libraries all aim to crowd out competitors from limited audience attention.

  • Infrastructure lock-in: Olympic bids, college facilities, and broadcasting rights create long-term structural advantages that persist beyond the initial spending

  • Deterrence signaling: Bloomberg's billion-dollar primary campaign and Formula 1 budgets send signals that make potential competition seem futile.


The point is that although the escalation of spending worries many, it is an established strategic move.


AI Capex is a Time-Tested Moat-Building Move

Investors might be quite concerned about the vast expansion of capital investment being made by some hyperscalers to support their artifici...